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Related lectures (15)
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Quasi-newton optimization
Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.
Optimization Methods
Covers optimization methods without constraints, including gradient and line search in the quadratic case.
Optimal Control: KKT Conditions
Explores optimal control and KKT conditions for non-linear optimization with constraints.
Optimization with Constraints
Covers the optimization with constraints and the KKT theorem.
Optimization Methods
Covers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.
Numerical analysis
Covers advanced numerical analysis topics including deep neural networks and optimization methods.
Runge Kutta Method
Covers the Runge Kutta method and its application to optimal control and neural networks.
Structural Analysis: Trusses
Covers the analysis of trusses, defining node positions, connectivity matrices, and stiffness matrices.
Deep Neural Networks: Optimization and Approximation
Explores optimization and approximation in deep neural networks, including optimal control and numerical experiments.
Linear Algebra: Compositions of Applications
Explores compositions of applications and injectivity conditions in linear algebra, including restriction of applications and combinatorial proof of injections.
